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bio-flow-cytometry-fcs-handling

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Read and manipulate Flow Cytometry Standard (FCS) files. Covers loading data, accessing parameters, and basic data exploration. Use when loading and inspecting flow or mass cytometry data before preprocessing.

OpenClawNanoClaw分析处理复现实验bio-flow-cytometry-fcs-handling🧬 bioinformatics (gptomics bio-* suite)bioinformatics — immunoinformatics & flow cytometryread

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-flow-cytometry-fcs-handling

维护者
FreedomIntelligence
许可
MIT
最近更新
2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • R：flowCore：：read.FCS() 或 flowCore：：read.flowSet() ，用于 multiple files。
  • Python：fcsparser.parse() 或 FlowCal.io.FCSData()。
  • Load my FCS files into R 或 Python" → Read Flow Cytometry Standard (FCS) files，access channel parameters 、 metadata，、 explore event data ，用于 downstream analysis. R：flowCore：：read.FCS() 或 flowCore：：read.flowSet() ，用于 multiple files Python：fcsparser.parse() 或 FlowCal.io.FCSData()。
  • fcs <- read.FCS('sample.fcs'，transformation = FALSE，truncate_max_range = FALSE)。

原始文档

SKILL.md 摘录

Load FCS Files

Goal: Read a single FCS file and inspect its parameters and metadata.

Approach: Use flowCore's read.FCS with transformation disabled to load raw data, then examine parameter names and descriptions.

library(flowCore)

## Parameter names

colnames(fcs)  # Short names
pData(parameters(fcs))  # Full metadata including descriptions

Load Multiple Files

Goal: Read a batch of FCS files into a single flowSet container for uniform processing.

Approach: List FCS files from a directory and load them into a flowSet with read.flowSet.

适用场景

  • 适合在loading 、 inspecting flow 或 mass cytometry data before preprocessing时使用。

不适用场景

  • Do not rely on this catalog entry alone ，用于 installation 或 maintenance details。

上游相关技能

  • compensation-transformation - Apply compensation and transforms
  • gating-analysis - Define cell populations
  • clustering-phenotyping - Unsupervised analysis

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